Overall Statistics
Total Trades
7
Average Win
0.01%
Average Loss
-0.38%
Compounding Annual Return
1192.565%
Drawdown
1.700%
Expectancy
-0.322
Net Profit
3.326%
Sharpe Ratio
6.634
Loss Rate
33%
Win Rate
67%
Profit-Loss Ratio
0.02
Alpha
0
Beta
152.168
Annual Standard Deviation
0.253
Annual Variance
0.064
Information Ratio
6.592
Tracking Error
0.253
Treynor Ratio
0.011
Total Fees
$67.34
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Orders import *
from QuantConnect.Algorithm import *
from QuantConnect.Algorithm.Framework import *
from QuantConnect.Algorithm.Framework.Alphas import *
from QuantConnect.Algorithm.Framework.Execution import *
from QuantConnect.Algorithm.Framework.Risk import *
from QuantConnect.Algorithm.Framework.Selection import *
from Alphas.RsiAlphaModel import RsiAlphaModel
from Alphas.EmaCrossAlphaModel import EmaCrossAlphaModel
from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel
from datetime import timedelta
import numpy as np

### <summary>
### Show cases how to use the CompositeAlphaModel to define.
### </summary>
class CompositeAlphaModelFrameworkAlgorithm(QCAlgorithmFramework):
    '''Show cases how to use the CompositeAlphaModel to define.'''

    def Initialize(self):

        self.SetStartDate(2013,10,7)   #Set Start Date
        self.SetEndDate(2013,10,11)    #Set End Date
        self.SetCash(100000)           #Set Strategy Cash

        # even though we're using a framework algorithm, we can still add our securities
        # using the AddEquity/Forex/Crypto/ect methods and then pass them into a manual
        # universe selection model using Securities.Keys
        self.AddEquity("SPY")
        self.AddEquity("IBM")
        self.AddEquity("BAC")
        self.AddEquity("AIG")

        # define a manual universe of all the securities we manually registered
        self.SetUniverseSelection(ManualUniverseSelectionModel())

        # define alpha model as a composite of the rsi and ema cross models
        self.SetAlpha(CompositeAlphaModel(RsiAlphaModel(), EmaCrossAlphaModel()))

        # default models for the rest
        self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
        self.SetExecution(ImmediateExecutionModel())
        self.SetRiskManagement(NullRiskManagementModel())